Computational Robotic Materials Lecture Series

The boundary between computation and materials is fading. By embedding computation into materials, materials become computers and computers become materials. Combining this computing power with sensors and actuators that are co-located in the material, will enable objects with an unprecedented level of functionality such as novel prosthetic devices, robot sensors and actuators, or smart buildings, among others. Read more…

This seminar series features speakers that share a similar vision on the convergence of materials and computing and who propose novel computing paradigms that are grounded in substrates ranging from modular robots, DNA, bacteria, and ASICs and might drive the computational robotic materials of the future.

Many animals form groups and behave collectively, and we know it shows extreme diversity of dynamics and patterns. For example, migrant fish, like the sardine, or large birds such as cranes tend to make groups by aligning their headings and keeping a fixed mutual distance. Small birds such as sparrows fly in wandering, disordered aggregates. Insects, such as the mosquito, fly at random within spatially limited swarms.

How can we incorporate such diverse collective animal behavior in a common framework? In this colloquium, I will talk about a mathematical model of interactive motile elements inspired by the group behavior of animals. Considering physical properties of self-propelled element with mutual interactions, we propose simple kinetic equations based on Newton equation with accelerative, resistive, interactive force, and a relaxation equation to relax the difference between the heading angle and the velocity direction angle. In this system, we obtained several types of collective behavior, such as regular cluster motions, chaotic wandering and swarming of cluster without introducing random fluctuations.

I will also show a control parameter of this system. It is obtained by the introduction of dimensionless equations and analysis of the phase diagram. Using this parameter, I will mention the relation between the characteristic of the proposed model and actual animal behaviors.

Ken Sugawara is an Associate Professor at Tohoku Gakuin University. He received BS, MS and PhD degree in Information Science from Tohoku University, Japan in 1992, 1994 and 1997, respectively. His research interest includes the modeling of collective animal behavior and its application for collective robot systems.

The idea of building robots out of lots of tiny robots is compelling, but through the last ten years of research, we haven’t been able to come up with any convincing real-world applications for modular robotics. In a couple of months, however, we’ll be releasing Cubelets, a modular robotic construction kit that gives kids the ability to build their own models of complexity, parallelism, and emergence. I’ll demonstrate Cubelets and the programming system that we’re working on, and discuss how these technologies can change the way that people think about the world.

Dr. Erik Schweikhardt

Eric Schweikardt is the Design Director at Modular Robotics in Boulder, CO. He is a deliberate comprehensivist with a background in architecture, computation, and design. He spent a year as a post-doc at the Cornell Computational Synthesis Lab working on self-reconfiguring structures. His PhD is from the Computational Design Lab at Carnegie Mellon University where he worked on construction kits, modular robotics, and evolutionary algorithms for design.

Self-organization is ubiquitous in nature. In systems that exhibit self-organizing properties, simple objects interact in simple ways to produce complex structures or emergent behaviors. Examples of natural self-organizing systems abound on all scales, from the microscopic to the cosmologic. In biology, nature uses self-organization to great effect. In certain circumstances, cells self-organize into organisms and organisms self-organize into colonies, flocks, or societies. Despite its importance, self-organization is poorly understood.

In this talk, I will provide recent advances in self-assembling systems research, with a concentration on mathematical models and theoretical tools used to aid in understanding self-assembling systems, and present related experimental work from the fields of molecular biology and robotics.

Dr. Dustin Reishus

Dustin Reishus holds an NSF Computing Innovations Fellowship at the University of Colorado. His research area is self-assembly and self-organization with an emphasis on the theoretical foundations, fundamental limits, and potential applications of self-organizing systems. He received his Ph.D. from the University of Southern California in December, 2009 under the advisement of Professor Leonard Adleman where he was an NSF Graduate Research Fellow.

An increasing number of distributed systems may be viewed as spatial computers — collections of devices distributed to fill a physical space in which the difficulty of moving information between any two devices is strongly dependent on the distance between them. Examples include peer-to-peer wireless networks, engineered biological cells, wireless sensor networks, robotic swarms and reconfigurable computing platforms (e.g. FPGAs), as well as natural systems like animal swarms and cells during morphogenesis.

Spatial computers pose a major programming and control challenge due to their potential scale and radical decentralization. In this talk, I will present an approach in which we view the network as a discrete approximation of the physical space through which devices are distributed. Using this “amorphous medium” abstraction and a carefully chosen set of space-time primitives, the Proto spatial computing language allows a programmer to express global behaviors in terms of simple geometric computations. These are then automatically transformed into a program that uses local interactions between devices to robustly and scalably approximate the specified global behavior. I will illustrate this approach with applications in sensor networks, synthetic biology, and morphogenetic engineering.

Dr. Jacob Beal

Dr. Jacob Beal is a scientist at BBN Technologies. His research interests center on the engineering of robust adaptive systems, with a focus on modelling and control for spatial computing systems. Dr. Beal completed his PhD in 2007 under ProfessorGerald Jay Sussman at the MIT Computer Science and Artificial Intelligence Laboratory.

We are entering the beginning of a parallel programming crisis with no shortage of processors but no obvious efficient, simple and intuitive way to program them. In short, we need to figure out how to best program and design parallel and distributed computers. Against this backdrop, one thing that is clear is that software programming and hardware design have a lot to learn from each other. For example, software needs to be parallel by default and hardware needs to be abstract by design. Since 2004, I have built a number of hardware/software systems that exhibit some of the best of both worlds qualities. In this talk I will touch upon three of these systems in order of increasing complexity: Gooze, a streaming multimedia scripting language, Proto, a language for amorphous computing, and Snap, a language for programming asynchronous logic automata (ALA). The scope and details differ but the model for each is wiring together and producing hardware structures using procedural parameterization, and the goal for each is to increase the abstraction of design without greatly sacrificing the efficiency of the runtime. My talk is based on fruitful collaborations with Jacob Beal on Proto, Scott Greenwald on Snap, and the MIT Center for Bits and Atoms on ALA.

Dr. Jonathan Bachrach

Jonathan Bachrach is a research scientist at UC Berkeley and principle at Other Lab where he researches spatial, parallel and unconventional programming languages, computing and robotics. Before UC Berkeley and Other Lab, he was a research scientist at MIT for 8 years, held postdocs at Stanford and ICSI/Berkeley, and was a researcher at IRCAM in Paris, developing new musical platforms. He studied cognitive science, computer science, and visual arts, receiving a BS degree from the University of California at San Diego and MS and PhD degrees from the University of Massachusetts at Amherst.

Modular reconfigurable robots are built from many simple modules (similar to Lego bricks, or cells in mammals). They can “morph” to meet the demands of changing tasks and environments. These systems are rich in interesting problems including: distributed computation and control, modular design, reconfiguration planning, motion planning, and others.

I’ll also talk about a new project-based and experimental engineering curriculum at UPenn. Laboratory classes provide a steady progression of skills and independence, from freshman through junior year. Lecture material is formulated to support the laboratory activities, in contrast to the traditional approach where laboratory exercises are decoupled from or tangential to the lectures.

Prof. Mark Yim

Mark Yim is an Associate Professor at the University of Pennsylvania and MEAM Undergraduate Curriculum Chair. Prior to this, he was Principal Scientist at the Palo Alto Research Center (formerly Xerox PARC) where he established a group developing modular self-reconfigurable robots. His group has demonstrated modular robots that can form different shapes, jump, ride tricycles, climb stairs, poles and fences, manipulate objects and reassemble themselves after being kicked into pieces. His other research interests include biologically inspired mechanisms, flying robots and meso-scale MEMs devices. Honors include the Lindback Award for Distinguished Teaching in 2009, UPenn’s highest teaching honor; induction as a World Technology Network Fellow; IEEE Robotics and Automation Distinguished Lecturer; and induction to MIT’s Technology Review TR100 in 1999. He has over 40 patents issued (perhaps most prominent are ones related to the Sony PS2 and Microsoft Xbox joypad vibration control which resulted in US$100,000,000 in litigation and settlements) and over 60 publications.